31 Result(s)
within
Computer Systems Organization and Communication Networks
**zhi Li
Conference Paper
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Chapter and Conference Paper
Multi-agent Perception via Co-attentive Communication Mechanism
Multi-agent collaborative perception has the potential to significantly enhance perception performance by facilitating the exchange of complementary information among agents through communication. Effective co...
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Chapter and Conference Paper
Explaining Federated Learning Through Concepts in Image Classification
Federated learning is a machine learning framework that solves the problem of data silos under secure data protection measures and is gradually becoming a machine learning paradigm for future AI development. I...
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Chapter and Conference Paper
Test-and-Decode: A Partial Recovery Scheme for Verifiable Coded Computing
Coded computing has proven its efficiency in tolerating stragglers in distributed computing. Workers return the sub-computation results to the master after computing, and the master recovers the final computat...
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Chapter and Conference Paper
Minimum Assumption Reconstruction Attacks: Rise of Security and Privacy Threats Against Face Recognition
Facial Recognition (FR), despite its remarkable precision and advancements achieved through deep learning, exhibits vulnerability to security threats, specifically originating from deep generative models profi...
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Chapter and Conference Paper
RecAGT: Shard Testable Codes with Adaptive Group Testing for Malicious Nodes Identification in Sharding Permissioned Blockchain
Recently, permissioned blockchain has been extensively explored in various fields, such as asset management, supply chain, healthcare, and many others. Many scholars are dedicated to improving its verifiabilit...
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Chapter and Conference Paper
Prediction and Analysis of Mobile Phone Export Volume Based on SVR Model
Electronic products occupy an important position in the export structure of China’s trade, and mobile phone products occupy a place in the export of electronic products. With the change of China’s export trade...
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Chapter and Conference Paper
Rethinking Feature Context in Learning Image-Guided Depth Completion
Depth completion (DC) is a classical computer vision task, which aims to estimate the 3D structure of the observed scene by utilizing the sparse depth from the Lidar and the RGB image from the camera. Treating...
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Chapter and Conference Paper
A Full-Level Based Network to Detect Every Aircraft in Airport Scene
The rapid development of civil aviation has led to increasingly crowded airports. The complex airport environment and large number of aircraft make airport object detection a difficult task. Due to the large e...
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Chapter and Conference Paper
Multisymplectic Unscented Kalman Filter for Geometrically Exact Beams
This paper introduces an unscented Kalman filter for the dynamics of geometrically exact beams based on multisymplectic geometry and Hamel’s formalism for classical field theories. The presented approach is a ...
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Chapter and Conference Paper
Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations
Although cross-domain recommender systems (CDRSs) are promising approaches to solving the cold-start problem, most CDRSs require overlapped users, which significantly limits their applications. To remove the o...
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Chapter and Conference Paper
5G Wireless Network Digital Twin System Based on High Precision Simulation
For a long time, the wireless signals of the communication network are invisible and intangible, which brings difficulties in recognizing and maintaining the network
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Chapter and Conference Paper
Evaluating the Parallel Execution Schemes of Smart Contract Transactions in Different Blockchains: An Empirical Study
In order to increase throughput, more and more blockchains begin to provide the ability to execute smart contract transactions in parallel. However, there is currently no research work on evaluating parallel e...
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Chapter and Conference Paper
Nested Named Entity Recognition from Medical Texts: An Adaptive Shared Network Architecture with Attentive CRF
Recognizing useful named entities plays a vital role in medical information processing, which helps drive the development of medical area research. Deep learning methods have achieved good results in medical n...
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Chapter and Conference Paper
Information Utilization Ratio in Heuristic Optimization Algorithms
Heuristic algorithms are able to optimize objective functions efficiently because they use intelligently the information about the objective functions. Thus, information utilization is critical to the performa...
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Chapter and Conference Paper
An Improved Particle Swarm Optimization with Dual Update Strategies Collaboration Based Task Allocation
The task allocation problem is a hot topic in the field of multiple unmanned aerial vehicle (UAV). In this paper, we consider the task allocation in rescue scenarios and establish the optimization model. Then,...
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Chapter and Conference Paper
Design of Mixed Learning System of Tourism Planning Course Based on Mobile Terminal
There are defects in the processing and allocation of teaching resources in the current learning system, which leads to the phenomenon that the teaching information display is stuck and collapsed when the numb...
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Chapter and Conference Paper
Design of Spoken English Distance Teaching Training System Based on Virtual Reality Technology
At present, the spoken English long-distance teaching training system has not designed a dynamic dictionary for spoken English teaching training, which leads to a high occupancy rate of the system server hardw...
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Chapter and Conference Paper
Optimizing Frequency Reuse in Multibeam Satellite Communication Systems
Frequency reuse (FR) is one of the most effective approaches for mitigating co-channel interference and improving the capacity of communication systems. However, there are some difficulties in applying it in m...
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Chapter and Conference Paper
Joint Source-Channel Coding Scheme Based on UEP-Raptor
Raptor code is a solution used for forward error correction at the application layer during multimedia transmission. The amount of multimedia transmission data is huge. In order to transmit high-quality image ...
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Chapter and Conference Paper
Learning the Implicit Semantic Representation on Graph-Structured Data
Existing representation learning methods in graph convolutional networks are mainly designed by describing the neighborhood of each node as a perceptual whole, while the implicit semantic associations behind h...
